Why do we use correlation coefficients and not covariance to describe the statistical association between x & y? Question 29 options: Covariance refers to variation, but correlation refers to the relationship The correlation coefficient is scaled between 0 & 1, so it is easy to report between different data sets Covariance is too easy to understand and it's better to complicate things Correlation coefficients are much easier to calculate